Evidence map›Paper›PMID 33430450›Full record

ArticleMaterials (Basel, Switzerland)2021

Parametric Finite Element Model and Mechanical Characterisation of Electrospun Materials for Biomedical Applications.

Katarzyna Polak-Kraśna, Emilia Mazgajczyk, Pirjo Heikkilä, Anthimos Georgiadis

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Katarzyna Polak-KraśnaBiomechanics Research Centre, National University of Ireland, H91 TK33 Galway, Ireland.
Emilia MazgajczykFaculty of Mechanical Engineering, Centre of Advanced Manufacturing Technologies-Fraunhofer Project Center (CAMT-FPC), Wroclaw University of Science and Technology, 50-370 Wrocław, Poland.ORCID 0000-0002-6194-3235
Pirjo HeikkiläVTT Technical Research Centre of Finland Ltd., FI-02044 VTT Tampere, Finland.
Anthimos GeorgiadisInstitute of Product and Process Innovation, Leuphana University Lüneburg, 21339 Lower Saxony, Germany.ORCID 0000-0003-4092-8834

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electrospun materials, due to their unique properties, have found many applications in the biomedical field. Exploiting their porous nanofibrous structure, they are often used as scaffolds in tissue engineering which closely resemble a native cellular environment. The structural and mechanical properties of the substrates need to be carefully optimised to mimic cues used by the extracellular matrix to guide cells' behaviour and improve existing scaffolds. Optimisation of these parameters is enabled by using the finite element model of electrospun structures proposed in this study. First, a fully parametric three-dimensional microscopic model of electrospun material with a random fibrous network was developed. Experimental results were obtained by testing electrospun poly(ethylene) oxide materials. Parameters of single fibres were determined by atomic force microscopy nanoindentations and used as input data for the model. The validation was performed by comparing model output data with tensile test results obtained for electrospun mats. We performed extensive analysis of model parameters correlations to understand the crucial factors and enable extrapolation of a simplified model. We found good agreement between the simulation and the experimental data. The proposed model is a potent tool in the optimisation of electrospun structures and scaffolds for enhanced regenerative therapies.

Indexed as

electrospinningFEmodellingnonwovenpoly(ethylene oxide) (PEO)tensile testing

Identifiers

PMID33430450
PMCPMC7826732

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.